Discover the journey, values, and vision behind Canada's premier neural network programming blog.
Neural Net Explorer was founded in 2022 in Toronto's thriving tech ecosystem, during a pivotal moment in Canada's AI development landscape. What began as a small collaboration between Michael Thompson and Sarah Chen—graduate researchers at the University of Toronto's Vector Institute—quickly evolved into one of Canada's most respected resources for neural network implementation expertise.
As our readership grew from hundreds to thousands, we expanded our team to include industry professionals from Montreal's Mila institute and Vancouver's tech corridor, creating a truly national perspective on AI development practices. Today, our community spans every province, connecting Canadian developers with cutting-edge neural network techniques adapted for our unique technological and regulatory environment.
We believe in hands-on implementation over theoretical discussion. Every concept we present includes functioning code examples that readers can adapt for real projects.
We advocate for thoughtful AI deployment that considers Canadian values of fairness, transparency, and social benefit in every neural network architecture we discuss.
We believe knowledge thrives through sharing. Our content is designed to foster a supportive community of Canadian AI practitioners sharing insights and solutions.
We highlight Canadian AI research, address our unique regulatory frameworks, and showcase how neural networks can solve challenges specific to our northern environment.
The core members guiding our editorial vision and technical direction
With over 12 years in machine learning research, Michael previously led AI teams at Element AI and the Canadian Institute for Advanced Research before co-founding Neural Net Explorer. His specialization in reinforcement learning algorithms has contributed to breakthrough applications in robotics and autonomous systems. Michael holds a Ph.D. in Computer Science from McGill University with a focus on deep reinforcement learning.
Beyond his technical expertise, Michael is passionate about mentoring the next generation of Canadian AI developers and has established partnerships with universities across Ontario and Quebec to create neural network programming curriculums.
Sarah brings invaluable expertise from her tenure at the Vector Institute where she specialized in computer vision applications and transformer architectures. Her research on adapting vision transformers for Canadian wildlife conservation has been published in top AI conferences and implemented by Parks Canada. Sarah earned her M.Sc. in Machine Learning from the University of Toronto.
As Neural Net Explorer's research director, Sarah leads our technical review process and maintains our high standards for code quality and implementation accuracy. She champions diversity in Canada's AI community and organizes our annual women-in-AI hackathon.
At Neural Net Explorer, we maintain a rigorous editorial process to ensure our content delivers maximum practical value to Canadian AI developers. Every tutorial undergoes a three-stage technical review:
We prioritize depth over breadth, focusing on comprehensive implementation guidance rather than superficial overviews. Our tutorials include not just the "how" but the crucial "why" behind architectural choices, helping developers build true understanding rather than simply copying solutions.
The growing network of Canadian AI practitioners we're proud to serve
Our community extends beyond our digital presence through regular meetups and workshops hosted in Toronto, Montreal, Vancouver, and Calgary. These events bring together students, industry professionals, and academic researchers to share insights and foster collaboration in the Canadian AI ecosystem.
We're particularly proud of our mentorship program that has connected over 200 early-career AI developers with experienced practitioners, many of whom have gone on to launch successful careers at Canada's leading AI companies and research institutions.
Our team's impact on the Canadian AI research landscape
Published in Proceedings of the Canadian Conference on Artificial Intelligence (2024)
Journal of Sustainable Computing, Volume 12, Issue 4 (2023)
Conference on Natural Language Processing in Bilingual Contexts (2023)
A library of pre-trained NLP models specifically tuned for Canadian English and French, with support for code-switching patterns common in bilingual regions.
Framework for optimizing neural network inference on edge devices operating in extreme cold conditions, addressing thermal throttling and battery performance challenges.
Curated collection of urban data from Canada's largest city, designed for training computer vision and reinforcement learning models in urban planning applications.
Canadian Digital Media Awards (2024)
Technology Learning Association of Canada (2023)
Society for Canadian Technical Communicators (2023)